Data Sampling Method

What is sampling?

• Sampling is the process of collecting secondary data

• Sampling is a process used in statistical analysis in which a predetermined number of observations are taken from a larger sample

• Sampling is an active process of gathering observations

• Sampling is an active process of gathering observations with the intent of estimating a population variable.

There are 3 types of sampling methods

• True

• False

What are the two main types of sampling methods?

• Non- Probability

• Stratified

• Probability

• Systematic

What is the difference between Non- Probability and Probability sampling methods?

• probability gives the subjects of the population an equal chance of being selected and non- probability does not

• Non-Probability gives the subjects

  of the population an equal chance of being selected and probability does not

What are some advantages of probability sampling?

• Reduces the possibility of bias

• Has a good survey response rate

• Less costly and more convenient

Non- Probability sampling can be expensive and time consuming

• True

• False

What are the types of probability sampling?

• Simple Random, Stratified, Cluster & Convenience

• Stratified, Simple Random, Quota & Systematic

• Systematic, Simple Random, Cluster & Stratified

Which of the following are not types of non-probability sampling?

• Quota

• Cluster

• Stratified

• Snowball

• Judgement

What are the four types of non probability sampling?

• Snowball, judgement, convenience & cluster

• Judgement, quota, systematic & convenience

• Snowball, judgement, convenience and quota

• Quota, systematic, cluster and snowball

Which of the following is not true about simple random sampling?

• With simple random sampling, it is almost impossible to identify every member of the population

• You might not be able to select enough individuals with your characteristic of interest

• Each subject has an equal chance of being selected

• None of the above